Optical imaging sensors collect coordinate data from object surfaces and can be useful in a wide variety of automation applications, including shape acquisition, assembly, inspection, and autonomous device navigation. The collected image data points represent surface geometry in a sampled form. The optical odometer is an active optical sensor that measures relative motion of a moving platform.
Positioning is a key task in most field robotics applications and can be very challenging in GPS-denied environments. A common tactic in such cases is to position visually. Accurate knowledge of position is needed for successful completion of field robotics tasks. In known or highly structured environments, localization relative to a predetermined map is typically performed using sensors appropriate for correlating map features with observations. In outdoor scenarios, various positioning and navigation systems are utilized in conjunction with input from odometry integration.
Many applications present significant challenges for positioning strategies utilizing optical sensors, and the use of optical sensors in outdoor environments presents difficulties in terms of reliability. For example, reduced performance is experienced in poorly lit or dirty environments. For autonomous device navigation, due to performance and cost considerations, the sensor is located somewhat close to the ground, and is particularly susceptible to blockage or fouling by dirt, debris, grass clippings, and moisture.